Not offered in 2005.
Synopsis: This unit introduces the ideas and major methods of data mining using practical tools for mining and prediction: Bayesian Nets, Causal Nets, Clustering, Decision Trees, Support Vector Machines and Neural Networks. This unit introduces the basic ideas and methods of data mining Artificial and real-world data Probabilistic bit-cost prediction and "right"/"wrong" prediction Training and test data Clustering, Decision Trees, Bayesian nets, Neural Networks and Support Vector Machines
Assessment: Major project (50%); Practical examination (25%); Written examination (25%)
Contact Hours: 30 hours of lectures and 36 hours of supervised practical classes and project work 24 hours